Fault Propagation Model Research Articles

Analysis of Cascade Fault Optimization Based on Regional Fault and Traffic Reallocation in Complex Networks

With the development of complex networks and demand for information services, more and more businesses are turning to complex networks for their hosting needs. Due to the growing service, attention must be paid to the problem of complex network cascade failures. A cascade failure is a large-scale failure caused by several small-scale failures. This phenomenon initially attracted attention in the power grid field. Currently, complex network cascade failures also deserve attention. In this paper, we focus on mitigating the impact of cascade failures. First, we propose a model to simulate the cascade fault propagation process based on a virus propagation model. We introduce an SDN control plane to the communication network to monitor the overall network. We consider regional failures and optimize traffic redistribution strategies to reduce the impact of cascade failure. Finally, we compare several simulation results based on proposed fault propagation models. The mechanism, we proposed, shows better performance in the remaining available nodes and the remaining network traffic.

Fault diagnosis strategy of CNC machine tools based on cascading failure

To ensure the safe operation of CNC machines, a fault diagnosis strategy based on cascading failure is proposed. According to fault mechanism analysis, a directed graph model of fault propagation between components in machine tool systems is established. In this study, the interpretative structural model method is used to realize the hierarchical structure of fault propagation model by matrix transformation and decomposition. Subsequently, the PageRank algorithm is introduced to evaluate the failure effects of the machine tool system components. The Johnson method is then applied to correct the component fault sequence and establish the model of rate of occurrence of failures that is based on time correlation. Finally, the fault diagnosis strategy is formulated through the component rate of the occurrence of failure, fault influence and fault propagation model, to identify the main cause of the fault and provide the basis for fault diagnosis. In the end, a machine tool equipment is used as an example for application to verify the validity of the method.

The role of gravitational collapse in controlling the evolution of crestal fault systems (Espírito Santo Basin, SE Brazil) – Reply

A high-quality 3D seismic volume from offshore Espirito Santo Basin (SE Brazil) is used to assess the importance of gravitational collapse to the formation of crestal faults above salt structures. A crestal fault system is imaged in detail using seismic attributes such as curvature and variance, which are later complemented by analyses of throw vs. distance (T-D) and throw vs. depth (T-Z). In the study area, crestal faults comprise closely spaced arrays and are bounded by large listric faults, herein called border faults. Two episodes of growth are identified in two opposite-dipping fault families separated by a transverse accommodation zone. Statistical analyses for eighty-four (84) faults show that fault spacing is < 250 m, with border faults showing the larger throw values. Fault throw varies between 8 ms and 80 ms two-way time for crestal faults, and 60–80 ms two-way time for border faults. Fault length varies between ∼410 m and 1750 m, with border faults ranging from 1250 m to 1750 m. This work shows that border faults accommodated most of the strain associated with salt growth and collapse. The growth history of crestal faults favours an isolated fault propagation model with fault segment linkage being associated with the lateral propagation of discrete fault segments. Importantly, two episodes of fault growth are identified as synchronous to two phases of seafloor erosion, rendering local unconformities as competent markers of fault reactivation at a local scale. This paper has crucial implications for the understanding of fault growth as a means to assess drilling risk and oil and gas migration on continental margins. As a corollary, this work demonstrates that: 1) a certain degree of spatial organisation occurs in crestal fault systems; 2) transverse accommodation zones can form regions in which fault propagation is enhanced and regional dips of faults change in 4D.

Model-Based Probabilistic Reasoning for Self-Diagnosis of Telecommunication Networks: Application to a GPON-FTTH Access Network

Carrying out self-diagnosis of telecommunication networks requires an understanding of the phenomenon of fault propagation on these networks. This understanding makes it possible to acquire relevant knowledge in order to automatically solve the problem of reverse fault propagation. Two main types of methods can be used to understand fault propagation in order to guess or approximate as much as possible the root causes of observed alarms. Expert systems formulate laws or rules that best describe the phenomenon. Artificial intelligence methods consider that a phenomenon is understood if it can be reproduced by modeling. We propose in this paper, a generic probabilistic modeling method which facilitates fault propagation modeling on large-scale telecommunication networks. A Bayesian network (BN) model of fault propagation on gigabit-capable passive optical network-fiber to the home (GPON-FTTH) access network is designed according to the generic model. GPON-FTTH network skills are used to build structure and approximatively determine parameters of the BN model so-called expert BN model of the GPON-FTTH network. This BN model is confronted with reality by carrying out self-diagnosis of real malfunctions encountered on a commercial GPON-FTTH network. Obtained self-diagnosis results are very satisfying and we show how and why these results of the probabilistic model are more consistent with the behaviour of the GPON-FTTH network, and more reasonable on a representative sample of diagnosis cases, than a rule-based expert system. With the main goal to improve diagnostic performances of the BN model, we study and apply expectation maximization algorithm in order to automatically fine-tune parameters of the BN model from real data generated by a commercial GPON-FTTH network. We show that the new BN model with optimized parameters reasonably improves self-diagnosis previously carried out by the expert Bayesian network model of the GPON-FTTH access network.

The role of gravitational collapse in controlling the evolution of crestal fault systems (Espírito Santo Basin, SE Brazil)

A high-quality 3D seismic volume from offshore Espírito Santo Basin (SE Brazil) is used to assess the importance of gravitational collapse to the formation of crestal faults above salt structures. A crestal fault system is imaged in detail using seismic attributes such as curvature and variance, which are later complemented by analyses of throw vs. distance (T-D) and throw vs. depth (T-Z). In the study area, crestal faults comprise closely spaced arrays and are bounded by large listric faults, herein called border faults. Two episodes of growth are identified in two opposite-dipping fault families separated by a transverse accommodation zone. Statistical analyses for eighty-four (84) faults show that fault spacing is < 250 m, with border faults showing the larger throw values. Fault throw varies between 8 ms and 80 ms two-way time for crestal faults, and 60–80 ms two-way time for border faults. Fault length varies between ∼410 m and 1750 m, with border faults ranging from 1250 m to 1750 m. This work shows that border faults accommodated most of the strain associated with salt growth and collapse. The growth history of crestal faults favours an isolated fault propagation model with fault segment linkage being associated with the lateral propagation of discrete fault segments. Importantly, two episodes of fault growth are identified as synchronous to two phases of seafloor erosion, rendering local unconformities as competent markers of fault reactivation at a local scale. This paper has crucial implications for the understanding of fault growth as a means to assess drilling risk and oil and gas migration on continental margins. As a corollary, this work demonstrates that: 1) a certain degree of spatial organisation occurs in crestal fault systems; 2) transverse accommodation zones can form regions in which fault propagation is enhanced and regional dips of faults change in 4D.

Hierarchical fault propagation and control modeling for the resilience analysis of process system

Petroleum refining system is complex, non-linear, multivariate with a number of highly correlated process units. Petrochemical units are potentially prone to incidents that have catastrophic consequences such as explosion, leakage of toxic materials, and the stoppage of the production process. There exist strong nonlinear dynamic fault behaviors during fault propagation in petroleum refining system. Although fault propagation scenario-based accident analysis can be an effective means to help operators to find the root causes of the current abnormal event, it has not yet been analyzed from the resilience engineering (RE) perspective. Resilience engineering is a new method that can control incidents and limit their consequences. In this paper, hierarchical fault propagation model (HFPM) is proposed as an extension of the Infrastructure Resilience-Oriented Modeling Language (IRML). The main contribution that consists in the design of HFPM is to incorporate the dynamic behavior of fault propagation. The model is divided into two parts. The first part is static analysis for system structure features and the second part is dynamic analysis for fault evolution mechanism. The performance of the proposed model has been tested on atmospheric and vacuum distillation system. Based on the case study results illustrated in this paper, the proposed method can be used for fault propagation and control strategy analysis in petroleum refining system from the resilience engineering perspective and also be beneficial to the design and modifications of process plants which will enhance the process safety.

Impact of Neotectonism in the Discussion of Geomorphological Processes as a Feedback System: North Bengal Foothills, West Bengal

The ongoing research paper is concerned about the sensitive issue like neotectonism and its impact on the landscape development. It is a detail and micro level study of North Bengal Himalayan foothills where the effect of tectonism is precisely observed. The term, neotectonism was introduced by Obruchen (1948) to summarize the active tectonic processes including the last major tectonic configuration change and establishment of modern stress. The North Bengal Himalayan foothill are very much concerned about the neotectonism activities at last to present geological periods. It is the one of the active unstable area of NE India where faults/thrusts and presence of synformal axis are predominantly controlling the geomorphological landscape development. This frontal region of an active orogenic beltlikethe NE Himalaya is characterized by complex terrace morphology with fluvial aggradation, degradationandstrath terraces. The detail study is mainly about the lineaments, drainage sequences, thrusting zone and synformal depressed zone of the area. Near the Neora-Mal river valley, close to to the mountain front a thick supported boulder bed with huge angular boulders of gneisses are exposed near Neora valley of Samsing area. Concerning the fault zone area of Matiali scarp, it is very clearly observed the extended part of Garubathan thrust (MBT) under the Matiali formation near the upper part of Kurtiriver. But, in the middle part of the river, where the synformation axis is present, river terraces are magnificiently developed over two sides of R. Kurti near Matiali hat. Here, two terraces are well virtualized but the upper most flat terrain is designated as fan surface which is made of mainly by the sediments of Matialiformation. In this region, slope of the fan surface is southerly 2.1˚. In south of the Matiali scarp on the banks of R. Neora, Kurti, Murti raised terraces are distinctly observed as T1 and T2.There kinds of features have developed due to the active tectonic activities from last Pleistocene to recent Holocene. As an evidence , we can consider the recent seismic study with in meizoseismal zone of both the 1934 Bihar-Nepal and 1950 Assam earthquakes but last surface rupture with a recorded displacement of 14m of Chalsafault related to the historical earthquake in Nepal around 1100 AD (Kumar et.al. 2011). It is a positive feedback system where neotectonism and geomorphological landscape are well related and in a classical model of fault propagation; geomorphic evolution through the structure/process is present in respect of time and space.

A novel dynamics model of fault propagation and equilibrium analysis in complex dynamical communication network

To describe failure propagation dynamics in complex dynamical communication networks, we propose an efficient and compartmental standard-exception-failure propagation dynamics model based on the method of modeling disease propagation in social networks. Mathematical formulas are derived and differential equations are solved to analyze the equilibrium of the propagation dynamics. Stability is evaluated in terms of the balance factor G and it is shown that equilibrium where the number of nodes in different states does not change, is globally asymptotically stable if G⩾1. The theoretical results derived are verified by numerical simulations. We also investigate the effect of some network parameters, e.g. node density and node movement speed, on the failure propagation dynamics in complex dynamical communication networks to gain insights for effective measures of control of the scale and duration of the failure propagation in complex dynamical communication networks.

Identification of Pivotal Causes and Spreaders in the Time-Varying Fault Propagation Model to Improve the Decision Making under Abnormal Situation

Under abnormal conditions, timely and effective decisions of system recovery and protective measures are of great significance for safety-critical systems. The knowledge of the roles that network nodes play in the spreading process is crucial for developing efficient maintenance decisions; for singling out and preferential control, the ‘pivotal spreaders’ may be a way to maximize the chances to timely hinder the fault pervasion. Inspired by the inhomogeneous topological nature of a complex fault propagation network, this study is devoted to exploring the spreading capabilities of nodes regarding both structural connectivity and causal influence strength, so as to provide decisions of preferential recovery actions under specific fault scenarios. Specifically, the dynamic betweenness centrality and nonsymmetrical entropy are incorporated to adaptively measure the system-wide fault diffusion risk of a set of controllable fault events. In order to model the dynamics and uncertainties involved in the complex fault spreading process, we introduce the model of a dynamic uncertain causality graph, based on which solutions of time-varying structure decomposition and causality reduction are adopted to improve the reasoning efficiency. Verification experiments consisting of simulated calculation cases and generator faults of a nuclear power plant show empirically the effectiveness and applicability of this method in large-scale engineering practice. Copyright © 2014 John Wiley & Sons, Ltd.

The effect of multiple pre-existing weaknesses on formation and evolution of faults in extended sandbox models

Abstract High-resolution three-dimensional seismic data show that fault distribution and evolution in rift basins can be very complicated and inconsistent with the classic model of fault formation and propagation. Fault development in the presence of multiple pre-existing weaknesses is still not clearly studied. Trying to understand the role of multiple pre-existing weaknesses in sand models, two series of experiments were prepared. In the first series of models, the mechanical properties of pre-existing weaknesses were the same but their orientations were different, whereas in the second series of models, both mechanical properties and orientations were different. The basic characteristics of fault formation and evolution in a rift basin revealed by the models are as follows: 1) weakness-reactivated faults (faults that formed directly along and above the pre-existing weaknesses) and weakness-related faults (faults which are not located above the pre-existing weaknesses, but have similar orientation) form much earlier than weakness-unrelated faults. The order of formation of different weakness-reactivated faults is determined by the relative reactivation tendency factors (fa) of the weaknesses; 2) weakness-reactivated faults and weakness-related faults develop mainly along or parallel to pre-existing weaknesses. In contrast, weakness-unrelated faults develop nearly perpendicular to the extension direction; 3) a complicated fault system can form during a single extension phase in the presence of multiple pre-existing weaknesses; and 4) the mode of fault formation and propagation and the increase in length and number of faults have close ties to the nature of pre-existing weaknesses. Fault displacement and length do not have a power law relationship for the majority of faults, and there is no unique relationship for different kinds of faults. In addition to providing new insights to the formation of complex fault systems, the experiment results presented here could be reasonably explained using the Reactivation Tendency Theory. They can also be applied to the complicated fault system in rift basin.

Service Fault Diagnosis Algorithm in Network Virtualization Environment

PDF HTML阅读 XML下载 导出引用 引用提醒 网络虚拟化环境下的服务故障诊断算法 DOI: 10.3724/SP.J.1001.2012.04171 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金(60973108, 60902050, 61121061); 国家高技术研究发展计划(863)(2011AA05A116, 2011AA01A102); 国家教育部博士点基金(20110005110011) Service Fault Diagnosis Algorithm in Network Virtualization Environment Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:网络虚拟化环境下,底层网络的透明性造成虚拟网提供商不能诊断所有的虚拟网服务故障.为解决此问题,提出了基于映射关系的虚拟网服务故障传播模型.针对故障传播模型中故障集与症状集较大、网络环境动态和噪声大而导致的已有诊断算法误报率高、时间复杂度高的问题,基于网络虚拟化环境下症状内在相关性特点,提出了一种新的基于症状内在相关性的虚拟网服务故障诊断算法 SFDoIC(service fault diagnosis algorithm based oninherent correlation among symptoms).仿真实验结果表明,SFDoIC 算法能够很好地解决底层网络透明性造成的虚拟网服务故障难以定位的问题.SFDoIC 算法可以有效地降低诊断算法的误报率,显著缩短诊断算法的运行时间. Abstract:The virtual network provider (VNP) cannot diagnose all service faults of virtual networks, because thesubstrate network is transparent for VNP within the network virtualization environment. To solve this problem, thepaper presents a service fault propagation model based on mapping relationships. In terms of the large fault set, thelarge symptom set, and noisy and dynamic environments, which result in the higher false positive rate and thelonger running time of existing fault diagnosis algorithms, a service fault diagnosis algorithm based on inherentcorrelation among symptoms (SFDoIC), is proposed. Simulation results show that algorithm SFDoIC can solve thedifficult problems in fault diagnosis that are caused by the transparency of the substrate network for VNP,effectively reducing the false positive rate and decreasing running time. 参考文献 相似文献 引证文献

Probabilistic fault localization with sliding windows

Fault localization is a central element in network fault management. This paper takes a weighted bipartite graph as a fault propagation model and presents a heuristic fault localization algorithm based on the idea of incremental coverage, which is resilient to inaccurate fault propagation model and the noisy environment. Furthermore, a sliding window mechanism is proposed to tackle the inaccuracy of this algorithm in the presence of improper time windows. As shown in the simulation study, our scheme achieves higher detection rate and lower false positive rate in the noisy environment as well as in the presence of inaccurate windows, than current fault localization algorithms.

Fault slip distribution and fault roughness

SUMMARY We present analysis of the spatial correlations of seismological slip maps and fault topography roughness, illuminating their identical self-affine exponent. Though the complexity of the coseismic spatial slip distribution can be intuitively associated with geometrical or stress heterogeneities along the fault surface, this has never been demonstrated. Based on new measurements of fault surface topography and on statistical analyses of kinematic inversions of slip maps, we propose a model, which quantitatively characterizes the link between slip distribution and fault surface roughness. Our approach can be divided into two complementary steps: (i) Using a numerical computation, we estimate the influence of fault roughness on the frictional strength (pre-stress). We model a fault as a rough interface where elastic asperities are squeezed. The Hurst exponent Hτ, characterizing the self-affinity of the frictional strength field, approaches Hτ = H// −1, where H// is the roughness exponent of the fault surface in the direction of slip. (ii) Using a quasi-static model of fault propagation, which includes the effect of long-range elastic interactions and spatial correlations in the frictional strength, the spatial slip correlation is observed to scale as Hs = Hτ + 1, where Hs represents the Hurst exponent of the slip distribution. Under the assumption that the origin of the spatial fluctuations in frictional strength along faults is the elastic squeeze of fault asperities, we show that self-affine geometrical properties of fault surface roughness control slip correlations and that Hs = H//. Given that H// = 0.6 for a wide range of faults (various accumulated displacement, host rock and slip movement), we predict that Hs = 0.6. Even if our quasi-static fault model is more relevant for creeping faults, the spatial slip correlations observed are consistent with those of seismological slip maps. A consequence is that the self-affinity property of slip roughness may be explained by fault geometry without considering dynamical effects produced during an earthquake.

Genesis of folds in external zones: application of fault propagation fold model. Gafsa Basin example (southern central Tunisia)

The evolution of geological structures is related particularly to reactivation of preexisting fault, thus the importance of tectonic inheritance. Basing on stratigraphic and structural data in external zones leaving the example of Gafsa Basin (southern central Tunisia), we study the evolution of folds during tectonic phases. The structural and stratigraphic data prove that Gafsa Basin is subject for more than one tectonic phase where beginning by Cretaceous extension and reactivated by Atlasic compression. The combination of field results associated to that geomorphology confirms the application of “fault propagation model” as evolution mode of folds. The balanced of cross section, using numerical software Ramp E.M. 1.5.2, shows the importance of tectonic inheritance to interpret evolution of structures reliefs. The deformation increases related to reactivation of old normal fault. The most important deformation is observed in Jbal At Taghli presenting folds in the form of duplex resulted from conjugate activity of tear fault; it is the first interpretation of tear fault activity in surface in the scale of Tunisia. The application of fault propagation fold model to interpret fold genesis confirms the field data and proves the role of tectonic inheritance and reactivation of preexisting faults in the evolution of structures during different tectonic phases.

Fold–thrust belts: overlooked provinces or justifiably avoided?

Abstract This volume results from a conference intended to assess the exploration and exploitation primarily of onshore fold–thrust belts. These are commonly perceived as ‘difficult’ places to explore and therefore are often avoided by companies. However, fold–thrust belts host large oil and gas fields and barriers to effective exploration mean that substantial resources may remain. This volume shows how evaluation techniques have developed over time. It is possible in certain circumstances to achieve good 3D seismic data. Structural restoration techniques have moved into the 3D domain and simple thermal constraints can be enhanced by using more sophisticated palaeo-thermal indicators to more accurately model burial and uplift evolution of source and reservoirs. Awareness of the influence of pre-thrust structure and stratigraphy and of hybrid thick and thin-skinned deformation styles is supplementing the simplistic thin-skinned fault-bend and fault propagation models employed in earlier exploration. The ‘learning curve’ in fold–thrust belt exploration has not been steep and further improvement seems likely to be a slow, expensive and iterative process with information from outcrop, well penetration and slowly improving seismic data. Industry and academia need together to develop and continually improve the necessary understanding of subsurface geometries, reservoir and charge evolution and timing.

A dynamic model for fault nucleation and propagation in a mechanically layered section

When a mechanically layered section of rock is subject to a horizontal strain, faults often nucleate preferentially in one or more layers before propagating through the rest of the section. The result is a high density of small, low-throw faults within these layers, and a much smaller number of large, through-cutting faults which nevertheless accommodate most of the strain due to their much larger displacement. A dynamic model of fault nucleation and propagation has been created by combining analytical and finite element techniques to calculate the energy balance of these propagating faults. This model shows that: 1) faults may nucleate in either mechanically weak layers, or in stiff layers with a high differential stress; 2) fault propagation may be halted either by strong layers (in which the sliding friction coefficient is high), or by layers which deform by flow and thus have low differential stress. This model can predict quantitatively the horizontal strain required for faults to nucleate, and to propagate across mechanical layer boundaries. The model is able to explain the complex pattern of fault nucleation and propagation observed in a mechanically layered outcrop in Sinai, Egypt.

Design of Intelligent Fault Diagnostic System (FDS)

This research work presents useful framework and mechanism for integrated fault diagnostic system, or FDS. The proposed system is composed of three major subsystems: fault detection, root cause and consequence analyzer, and maintenance analyzer. Learning mechanisms are proposed to extract knowledge about deviations/failure modes from real time process and equipment monitoring data. Fault semantic network is proposed to represent failure modes and fault propagation models as integrated with process and equipment models. Qualitative rules are defined and associated with fault semantic networks for practical Actual maintenance findings are used to tune training data for more accurate fault detection and root cause and consequence analysis. Case study is used to illustrate the proposed idea.

Internet Services Fault Management: Layering Model and Algorithm

In window-based Internet service fault management,improper time window size setting will affect the fault diagnosis algorithm. In order to reduce the impact,challenges of Internet service fault management are analyzed in this paper,and a layering model is recommended. Bipartite graph is chosen to be the fault propagation model (FPM) for each layer. A window-based fault diagnosis algorithm MFD (multi-window fault diagnosis) is proposed for the bipartite FPM. MFD takes the correlation of adjacent time windows into account. As a result,it can reduce the impact of improper time window size setting. Simulation results prove the validity and efficiency of MFD.

Safety and reliability analysis in a polyvinyl chloride batch process using dynamic simulator-case study: Loss of containment incident

In this paper, a novel methodology in batch plant safety and reliability analysis is proposed using a dynamic simulator. A batch process involving several safety objects (e.g. sensors, controller, valves, etc.) is activated during the operational stage. The performance of the safety objects is evaluated by the dynamic simulation and a fault propagation model is generated. By using the fault propagation model, an improved fault tree analysis (FTA) method using switching signal mode (SSM) is developed for estimating the probability of failures. The timely dependent failures can be considered as unavailability of safety objects that can cause the accidents in a plant. Finally, the rank of safety object is formulated as performance index (PI) and can be estimated using the importance measures. PI shows the prioritization of safety objects that should be investigated for safety improvement program in the plants. The output of this method can be used for optimal policy in safety object improvement and maintenance. The dynamic simulator was constructed using Visual Modeler (VM, the plant simulator, developed by Omega Simulation Corp., Japan). A case study is focused on the loss of containment (LOC) incident at polyvinyl chloride (PVC) batch process which is consumed the hazardous material, vinyl chloride monomer (VCM).

An alarm management framework for automated network fault identification

Many timing constraint (or real-time) distributed systems, such as real-time database systems, are now being used in safety critical applications. However, they are subject to system failures caused by the malfunction of underlying network components. Without the helps of network experts or sophisticated management tools, most users cannot resolve these network problems by themselves. Sometimes, worse, it is usually prohibited to use these management tools, e.g. the ‘ping’ command, for the security sake. Accordingly, we develop a management system to automate network fault identification merely based on the analysis of the abnormal events from the monitored timing constraint distributed system. In this system, a fault identification framework is designed to identify automatically faulty network elements by using a two-level fault propagation model which combines Timing Constraint Petri nets with an alarm clustering mechanism. In addition, the concepts of redundant/ringleader alarms and innocent network elements are also introduced into the framework to obtain an effective diagnosis. At last, the management system is implemented according to the framework to demonstrate the performance of our fault identification.